corpus (version 0.8.0)

as_text: Text Vectors

Description

Create or test for text objects.

Usage

as_text(x, filter = text_filter(x), ...)
    is_text(x)

Arguments

x

object to be coerced or tested.

filter

text filter object for the converted text.

…

further arguments passed to or from other methods.

Value

as_text attempts to coerce its argument to text type and set its text_filter property; it strips all other attributes except for names.

is_text returns TRUE or FALSE depending on whether its argument is of text type or not.

Details

The corpus_text type is a new data type provided by the corpus package suitable for processing Unicode text. Text vectors behave like character vectors (and can be converted to them with the as.character function). They can be created using the read_ndjson function or by converting another object using the as_text function.

All text objects have a text_filter property specify how to transform the text into tokens or segment it into sentences.

The default behavior for as_text is to proceed as follows:

1. If x is a character vector, then we create a new text vector from x, preserving names(x) if they exist.

2. If x is a data frame, then we call as_text on x$text if a column named "text" exits in the data frame. We set the names of the result to the data frame's row names, if they exist. If the data frame does not have a column named "text", then we fail with an error message.

3. If x is a corpus_text object, then we drop all attributes from the object except for its names and filter, and we set the object class to corpus_text.

4. The default behavior for when none of the above conditions are true is to call as.character on the object first, and call as_text on the returned character object.

In all cases, we set the text_filter property of the result to the filter argument given to as_text.

Note that the special handling for the names of the object is different from the other R conversion functions (as.numeric, as.character, etc.), which drop the names.

as_text is generic: you can write methods to handle specific classes of objects.

See Also

as_utf8, text_filter, read_ndjson.

Examples

# NOT RUN {
    as_text("hello, world!")
    as_text(c(a="goodnight", b="moon")) # keeps names

    is_text("hello") # FALSE, "hello" is character, not text
# }